{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing the Titanic Disaster"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introduction:\n",
    "\n",
    "This exercise is based on the titanic Disaster dataset avaiable at [Kaggle](https://www.kaggle.com/c/titanic).  \n",
    "To know more about the variables check [here](https://www.kaggle.com/c/titanic/data)\n",
    "\n",
    "\n",
    "### Step 1. Import the necessary libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2. Import the dataset from this [address](https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/07_Visualization/Titanic_Desaster/train.csv) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 3. Assign it to a variable titanic "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4. Set PassengerId as the index "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Survived  Pclass  \\\n",
       "PassengerId                     \n",
       "1                   0       3   \n",
       "2                   1       1   \n",
       "3                   1       3   \n",
       "4                   1       1   \n",
       "5                   0       3   \n",
       "\n",
       "                                                          Name     Sex   Age  \\\n",
       "PassengerId                                                                    \n",
       "1                                      Braund, Mr. Owen Harris    male  22.0   \n",
       "2            Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0   \n",
       "3                                       Heikkinen, Miss. Laina  female  26.0   \n",
       "4                 Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0   \n",
       "5                                     Allen, Mr. William Henry    male  35.0   \n",
       "\n",
       "             SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
       "PassengerId                                                          \n",
       "1                1      0         A/5 21171   7.2500   NaN        S  \n",
       "2                1      0          PC 17599  71.2833   C85        C  \n",
       "3                0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "4                1      0            113803  53.1000  C123        S  \n",
       "5                0      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 5. Create a pie chart presenting the male/female proportion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWlJBiYhIWvo/rI6mZkORh2MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117e78690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 6. Create a scatterplot with the Fare payed and the Age, differ the plot color by gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-5, 85)"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZkAAAFqCAYAAADIoyd5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a678c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 7. How many people survived?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "342"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 8. Create a histogram with the Fare payed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEZCAYAAACEkhK6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAHCZJREFUeJzt3X2UXHWd5/F3JyRIoBOINoyiEkX54uKihgfFE3kQGWUU\n0T26zq7ogEpGBgFdRQUH3Tk7UVYGlaDLMBBBZp1RYRFBBoEZGCTqKI9qBL+E5xlFCQTyYALppHv/\nuLehklQnv+5OdVVXv1/n5KTq1q1b328nXZ/63d+9t3oGBweRJGlrprS7AEnSxGBgSJKKGBiSpCIG\nhiSpiIEhSSpiYEiSimzX7gI0uUTEAPBLYKBeNAjcmpnzW/BaewD3Ab+oF/XUfy/MzIuarH8UcHhm\nfnQbvPafAe/KzKM2WX4jcG5mXh4RtwOHZubKYbYxE/huZh4+1nqkbcHA0HgbpHqTfGKcXm9NZs4d\nuhMRLwCWRMQtmbmkccXMvAq4ahu+9hZPcmqsaxizgQO2XTnS2BgYGm89PPtJfyMR8QFgPjCN6s3y\nzMw8v/60/kFgR+DJzDw8Ij4InFBv63HgpMzMrb14Zv42IpYCe0XEfo3bBS6hHhVExG7A3wJ7AxuA\n8zPz3PpT/znAK+s6/wU4NTMHmrzcFtWjrefV27kEeG790NWZ+Tng68CMeiSyP7AWuALYF3hvXfcX\ngR2AdcAZmXltREwB/gY4qu7rZ8ArMvON9QhnORDAecCt9TamA88Hrs/M4+vR2Q31n4Oo3itOBf68\n/pncmpl/OtKeNbE5h6F2uDEibo+IO+q/nxcRO1K9eR+ZmfsBfwqc1fCc/wQcXIfFwcD7gXn1umcB\nl5e8cEQcBOwJ/HTT7db3h0YF5wGZma8AXg8cHxEvBb5M9WZ5ADAX6AM+PszLHVz3N/TnDmC/hseH\nXut44L7M3B84GHh5RPQCx1GPkOpAmgZ8r67pQeBSqqB8NXAs8H/rN/rjgdfUvQ3122h5Zr4yM78G\nnEwVNAcB+wBHR8Rr6vVeAlyRma+kCo6vAO+p13tDRLxumL7VpRxhqB2a7pKq5xDeFhEvB15N9Ql6\nyC8y8w/17bdSvQn+OCKGRis7R8TOmfnkJpsd+oTeQ/X/fRnw3zPzNxGx6XYbHQ58AqCeY9i3rvFt\nwAER8aF6vecw/K6nH2bm2zfp8caGu0O1/wC4un6z/2fg05m5KiJmN9nm4vrv1wJLM/PWusa7ImIx\ncBhwJHBJZvbXr3k+cFLDNm5uuH0s8CcRcRrVyGEHYCeqUci6zLy6Xu8+4MdDP6uI+C3VKFCTiIGh\ndthsl1RE7A78BDif6g3tMqpgGLK64fZU4O8z87TG5zcJC9hkDqOJ1cMsX09DEETES4DHqEbl7x7a\n/VXvohrTBdky89Z6+28C3gjcEhFHA49sod5mewemUv1O97Pxz3jDMNuAKoDuoAqt71AF0dBz123y\nvP4td6Ju5y4pdYr9gUczc0FmXk+1/52GEUSj64D/FhF/VK/zF1SfzJtpOl9S4HqqXUJExCyquYqX\nAdcC/6Nevj3VJPlHRvka1Nv5AvDZzLyyPkLrV8BeVKE1dZin/Vv11Ni/3sY+wBuAfwX+CTgmIqZH\nxHZUo4jNQi0idqbarfapzLwCeGHd49BrjvZnpy7lCEPjbbhP49cBx0VEUn0C/hnV7qOXbbpiZl4X\nEf8buD4iNgArgXeO8PW25iTgvIj4OdUb54LMvCMiTgG+EhG/pPr9uZ5q0rjUYJPbXwG+ERG/AJ4G\nfg78I9XI4I6IuAuY1/jczHw8It4NfDUiZtTrHpuZ90bEfVST2rdT/SwfANZs+vqZ+WQdVndExGNU\nI6jFVD/z+9nyz87LXE9CPV7eXOouEXEEsGtmfrO+/xVgbeMuPGk0WhoY9eF9F1B92hkAPkx1+N73\ngXvq1c7LzEsj4niqQyr7qT7NXd1kk5K2oj7X5GJgV6pR0J3ACZm5qp11aeJrdWAcDRyVmR+KiEOA\nj1Ht852ZmV9uWG83qqH9XGAG1bB4v6GjPCRJ7dfSOYzM/F5EDJ05Owd4guo49IiId1CNMj4GHAgs\nzsz1wMr6xKp9gdtaWZ8kqVzLj5LKzIGIuJjq7NhvUp0w9YnMPIRqYu1zwExgRcPTVgOzWl2bJKnc\nuBwllZnHRsSuVEe+HJSZQ8eXXwEsBG6iCo0hvVSXNBjW4ODgYE+PR/1J0giN+o2zpYEREccAL8zM\nM4GnqCa+L4+IkzPzFqqzaW8DbgEWRMR0qjNN9waWDLNZAHp6eli2rHvn8Pr6eu1vgurm3sD+Jrq+\nvt5RP7fVI4zLgYsi4qb6tU4B/p3q2PF1wO+A+Zm5OiIWUk129wCnZ+amZ5lKktqo1ZPea6guVrap\neU3WXQQsamU9kqTR89IgkqQiBoYkqYiBIUkqYmBIkopM2KvVnnL6WfRMec5Gy3qfM4WT//z9bapI\nkrrbhA2Mu37bw3Oe++KNls1ccc8wa0uSxspdUpKkIgaGJKmIgSFJKmJgSJKKGBiSpCIGhiSpiIEh\nSSpiYEiSihgYkqQiBoYkqYiBIUkqYmBIkooYGJKkIgaGJKmIgSFJKmJgSJKKGBiSpCIGhiSpSEu/\nojUipgAXAAEMAB8GngYuru8vycwT63WPB+YD/cCCzLy6lbVJkkam1SOMo4DBzJwHnAF8HvgScHpm\nHgJMiYijI2I34CTgIOAtwBciYlqLa5MkjUBLAyMzv0c1agDYA3gCmJuZN9fLrgGOAA4EFmfm+sxc\nCSwF9m1lbZKkkWnpLimAzByIiIuBdwDvpgqIIauAmUAvsKJh+Wpg1khfa9q0qfT19Y6+2A7TTb00\n0839dXNvYH+TVcsDAyAzj42IXYFbgB0aHuoFngRWUgXHpstHpL9/A8uWrRpLqR2jr6+3a3ppppv7\n6+bewP4murGEYUt3SUXEMRHx6fruU8AG4NaIOKRediRwM1WQzIuI6RExC9gbWNLK2iRJI9PqEcbl\nwEURcVP9WicDvwYurCe17wYuy8zBiFgILAZ6qCbF17W4NknSCLQ0MDJzDfCeJg8d2mTdRcCiVtYj\nSRo9T9yTJBUxMCRJRQwMSVIRA0OSVMTAkCQVMTAkSUUMDElSEQNDklTEwJAkFTEwJElFDAxJUhED\nQ5JUxMCQJBUxMCRJRQwMSVIRA0OSVMTAkCQVMTAkSUUMDElSEQNDklTEwJAkFTEwJElFDAxJUhED\nQ5JUZLtWbTgitgO+DswBpgMLgH8Hvg/cU692XmZeGhHHA/OBfmBBZl7dqrokSaPTssAAjgEey8z3\nR8QuwJ3AXwFnZ+aXh1aKiN2Ak4C5wAxgcURcl5n9LaxNkjRCrQyM7wCX1renUI0e9gP2joh3UI0y\nPgYcCCzOzPXAyohYCuwL3NbC2iRJI9SywMjMNQAR0UsVHH8JbA9cmJl3RMRpwOeoRh4rGp66Gpg1\nmtecNm0qfX29Y6q7k3RTL810c3/d3BvY32TVyhEGEfEi4HLgq5n5rYiYlZlD4XAFsBC4CZjZ8LRe\n4MnRvF5//waWLVs1lpI7Rl9fb9f00kw399fNvYH9TXRjCcOWHSVVz01cC3wyM79RL742Ivavbx9O\ntdvpFmBeREyPiFnA3sCSVtUlSRqdVo4wTgN2Bs6IiM8Cg1RzFl+JiHXA74D5mbk6IhYCi4Ee4PTM\nXNfCuiRJo9DKOYyPAh9t8tC8JusuAha1qhZJ0th54p4kqYiBIUkqYmBIkooYGJKkIgaGJKmIgSFJ\nKmJgSJKKGBiSpCIGhiSpiIEhSSpiYEiSihgYkqQiBoYkqYiBIUkqYmBIkooYGJKkIgaGJKmIgSFJ\nKmJgSJKKGBiSpCLblawUEf8EXARckZn9rS1JktSJSkcYZwJvAZZGxNci4oAW1iRJ6kBFI4zM/CHw\nw4jYAXgX8P8iYiVwIXBeZj7dwholSR2gKDAAIuJQ4H3AHwPXAN8GjgCuBN7cZP3tgK8Dc4DpwALg\nLuBiYABYkpkn1useD8wH+oEFmXn1KPuRJLVI6RzGQ8D9VPMYH8nMtfXyfwVuGeZpxwCPZeb7I2Jn\n4OfAncDpmXlzRJwXEUcD/wacBMwFZgCLI+I650okqbOUjjDeCKzKzEcjYoeIeFlm3puZG6je6Jv5\nDnBpfXsqsB6Ym5k318uuoRqtDACLM3M9sDIilgL7AreNoh9JUouUTnq/FfhBfXtX4KqImL+lJ2Tm\nmsz8Q0T0UgXHZ4CehlVWATOBXmBFw/LVwKzCuiRJ46R0hDEfeC1AZj4UEfsBPwX+bktPiogXAZcD\nX83Mb0XEFxse7gWeBFZSBcemy0ds2rSp9PX1juapHambemmmm/vr5t7A/iar0sCYBjQeCbUOGNzS\nEyJiN+Ba4MTMvLFefEdEHFwfdXUkcAPVHMiCiJgO7ADsDSwpb+FZ/f0bWLZs1Wie2nH6+nq7ppdm\nurm/bu4N7G+iG0sYlgbGFcANEfGd+v5/oTo6aktOA3YGzoiIz1IFzCnAuRExDbgbuCwzByNiIbCY\napfV6Zm5boR9SJJarPQ8jE9FxLuAQ6gOfV2YmVds5TkfBT7a5KFDm6y7CFhUUoskqT1Gci2pu6mO\nfLoCWB4RB7emJElSJyo9D+NrwFHAfQ2LB6kOt5UkTQKlcxh/DMTQCXuSpMmndJfU/Wx8DoUkaZIp\nHWEsB+6KiB8DTw0tzMwPtKQqSVLHKQ2MH/Dsmd6SpEmo9LDab0TEHGAfqpPxXpSZD7SyMElSZyma\nw4iI9wBXAecAs4GfRMQxrSxMktRZSie9PwW8nvqKtcBrqM7kliRNEqVzGBsyc1VEAJCZj0TEQOvK\nGp2BgQHuu2/pZsvnzHkpU6dObUNFktQ9SgPjVxHxEWBaRLwa+AuqL0PqKKtXPM4pZ13JjFm7PrNs\nzYpHOefUt7Pnni9vY2WSNPGVBsaJwF8Ca6m+dvUG4OOtKmosZszalZ122b3dZUhS1yk9SuoPVHMW\nzltI0iRVei2pATb//otHMvOF274kSVInKh1hPHM0Vf1dFu8ADmpVUZKkzjOSy5sDkJn9mXkpXqlW\nkiaV0l1S72+420N1xrffiidJk0jpUVKHNdweBB4D3rPty5EkdarSOYzjWl2IJKmzle6SeoDNj5KC\navfUYGa+dJtWJUnqOKW7pP4BeBq4AOgH3gscAHymRXVJkjpMaWC8OTP3b7h/TkTclpkPtaIoSVLn\nKT2stici3jR0JyLeBqxsTUmSpE5UOsKYD1wSEX9ENZfxa+DPWlaVJKnjlB4ldRuwT0Q8D3gqM1eX\nvkBEvBY4MzMPq690+33gnvrh8zLz0og4niqU+oEFmXn1iLqQJLVc6VFSewAXAnOAN0TElcAHMvPB\nrTzvVOB9wFDA7AecnZlfblhnN+AkYC4wA1gcEddlZv/IWpEktVLpHMb5wFlUb/y/B/4RuKTgefcC\n72y4vx/w1oi4KSIuiIidgAOBxZm5PjNXAkuBfUsbkCSNj9LAeF5mXgeQmYOZeQEwc2tPyszvAusb\nFv0UODUzDwHuBz5Xb2dFwzqrgVmFdUmSxknppPfaiHgh9cl7ETGP6ryMkboiM4fC4QpgIXATG4dP\nL/DkKLbNdtOafw3r7Nk70dfXO5pNttVErHkkurm/bu4N7G+yKg2Mj1FNVu8ZEXcCs4F3j+L1ro2I\nj2TmrcDhwG3ALcCCiJgO7ADsDSwZxbZZ378Bpm++fPny1Sxbtmo0m2ybvr7eCVfzSHRzf93cG9jf\nRDeWMCwNjN2ozuzeC5gK/DozR3O12hOAcyNiHfA7YH5mro6IhcBiqkuNnD7KbUuSWqg0ML5YH+r6\nq5G+QH02+Ovr23cA85qsswhYNNJtS5LGT2lg3BcRX6eatF47tDAzS46UkiR1gS0eJRURu9c3H6fa\nXfQ6qu/GOAw4tKWVSZI6ytZGGFcBczPzuIj4eGaePR5FSZI6z9bOw+hpuP3eVhYiSepsWxthNH5p\nUs+wa3WwwYEBHn64+VXY58x5KVOnNj93Q5K0sdJJb2j+jXsdb+2qZZz97ceYMeuRjZavWfEo55z6\ndvbc8+VtqkySJpatBcY+EXF/fXv3htsT6qtZZ8zalZ122X3rK0qShrW1wNhrXKqQJHW8LQaGX8Eq\nSRpSerVaSdIkZ2BIkooYGJKkIgaGJKmIgSFJKmJgSJKKGBiSpCIGhiSpiIEhSSpiYEiSihgYkqQi\nBoYkqYiBIUkqYmBIkooYGJKkIiP5itZRiYjXAmdm5mERsSdwMTAALMnME+t1jgfmA/3Agsy8utV1\nSZJGpqUjjIg4FbgA2L5e9CXg9Mw8BJgSEUdHxG7AScBBwFuAL0TEtFbWJUkauVbvkroXeGfD/f0y\n8+b69jXAEcCBwOLMXJ+ZK4GlwL4trkuSNEItDYzM/C6wvmFRT8PtVcBMoBdY0bB8NTCrlXVJkkau\n5XMYmxhouN0LPAmspAqOTZeP2HbTpo5o/dmzd6Kvr3c0LzUuOrm2baGb++vm3sD+JqvxDozbI+Lg\nzPwhcCRwA3ALsCAipgM7AHsDS0az8fX9G2B6+frLl69m2bJVo3mpluvr6+3Y2raFbu6vm3sD+5vo\nxhKG4x0YnwAuqCe17wYuy8zBiFgILKbaZXV6Zq4b57okSVvR8sDIzIeA19e3lwKHNllnEbCo1bVI\nkkbPE/ckSUUMDElSEQNDklTEwJAkFTEwJElFDAxJUhEDQ5JUxMCQJBUxMCRJRQwMSVIRA0OSVMTA\nkCQVMTAkSUUMDElSEQNDklTEwJAkFTEwJElFDAxJUpHx/k7vjjE4MMDDDz+02fI5c17K1KlT21CR\nJHW2SRsYa1ct4+xvP8aMWY88s2zNikc559S3s+eeL29jZZLUmSZtYADMmLUrO+2ye7vLkKQJwTkM\nSVIRA0OSVMTAkCQVacscRkTcBqyo7z4AfB64GBgAlmTmie2oS5I0vHEfYUTE9gCZ+cb6zweBLwGn\nZ+YhwJSIOHq865IkbVk7RhivAnaMiGuBqcBngLmZeXP9+DXAEcD32lCbJGkY7ZjDWAOclZlvBk4A\nvgn0NDy+CpjVhrokSVvQjhHGPcC9AJm5NCIeB+Y2PN4LPDmaDW83bexnaM+evRN9fb1j3s620Cl1\ntEo399fNvYH9TVbtCIwPAP8ZODEiXgDMBK6LiEMy8ybgSOCG0Wx4ff8GmD624pYvX82yZavGtpFt\noK+vtyPqaJVu7q+bewP7m+jGEobtCIxFwEURcTPVUVHHAo8DF0bENOBu4LI21CVJ2oJxD4zM7AeO\nafLQoeNciiRpBDxxT5JUxMCQJBWZ1FerLbVhwwYefPD+po/5/RmSJgsDo8CDD97PKWddyYxZu260\n3O/PkDSZGBiF/O4MSZOdcxiSpCIGhiSpiIEhSSriHMY25hFVkrqVgbGNeUSVpG5lYLSAR1RJ6kbO\nYUiSihgYkqQiBoYkqYiBIUkqYmBIkop4lNQYDA4M8PDDD220bNP7ktQtDIwGzQIAhg+BtauWcfa3\nH2PGrEeeWfb4f9zNc1/4iuJtezKfpInCwGjQLABg+BCAzc+5WLPi98Xb9mQ+SROJgbGJZifdDRcC\n22LbkjRROOktSSpiYEiSirhLqo2GmwgHmD37VRvdH+lVcIdbf6zrSpq8DIw2Gm6Sfc2KR/n7L+zE\nLrs8/5llI70KbrP1t8W63cLL0Esj1zGBERE9wP8BXgU8BXwoM5v/RneRZhPhgwMDPPDAAyxfvvqZ\nZQ8//NCw6w53KPBIJtnbPSE/3Bv4hg0bgB6mTt147+lY39S9DL00ch0TGMA7gO0z8/UR8VrgS/Wy\nSWftqmV89u8e2+jNbLhDe0dzKHAnGu4N/PH/uJsdep/bktFPu0NSE4e7bSudFBjzgB8AZOZPI2L/\nNtfTVqXndzRbd7j1R3Ji4pbmV1r1SzJcH6Vv7O5mUqtMxt22zXRSYMwEVjTcXx8RUzJzoNnKg6sf\nYoCnNlo2sHY5a9bO2GjZ2lXLgZ7Nnt9s+UjW3RbbGO/alv82+esL7uI5O83eaPmK39/Pzs/fq2jd\np1Yv5y+PP4IXv3iPzV5zJJ54YqfNdrmtWfFoUR9rVjw6bPD99QXXF9U83OsNt+2R2LS3bjMZ+xvu\n/0QnXwqoFUHWMzg4uM03OhoRcTbwk8y8rL7/cGa+uM1lSZJqnXQexo+APwGIiNcBv2xvOZKkRp20\nS+q7wBER8aP6/nHtLEaStLGO2SUlSepsnbRLSpLUwQwMSVIRA0OSVKSTJr2LdNslROqz2s/MzMMi\nYk/gYmAAWJKZJ9brHA/MB/qBBZl5dbvqLRUR2wFfB+YA04EFwF10QX8RMQW4AAiqXj4MPE0X9NYo\nInYFbgXeBGygi/qLiNt49ryvB4DP0139fRp4OzCN6v3yh2yD/ibiCOOZS4gAp1FdQmRCiohTqd54\ntq8XfQk4PTMPAaZExNERsRtwEnAQ8BbgCxExrS0Fj8wxwGOZeTBV3V+le/o7ChjMzHnAGVRvNt3S\nG/BM4P8tsKZe1DX9RcT2AJn5xvrPB+mu/g4BDqrfIw8FXsw26m8iBsZGlxABJvIlRO4F3tlwf7/M\nvLm+fQ1wBHAgsDgz12fmSmApsO/4ljkq36F6MwWYCqwH5nZDf5n5PapPZQB7AE/QJb01+BvgPOC3\nVKfad1N/rwJ2jIhrI+Kf61F+N/X3ZmBJRFwBXAl8n23U30QMjKaXEGlXMWORmd+leiMd0ngNjFVU\nvfaycb+rgVmtr25sMnNNZv4hInqBS4HP0F39DUTExcBC4B/oot4i4ljg0cy8nmf7avwdm9D9UY2a\nzsrMNwMnAN+ki/79gOcB+wHv4tn+tsm/30R8o11J1eiQYa83NQE19tELPEnV78wmyzteRLwIuAH4\nRmZ+iy7rLzOPBfYCLgR2aHhoovd2HNVJtDdSfRq/BOhreHyi93cP1ZsombkUeBzYreHxid7f48C1\n9cjhHqq53sYgGHV/EzEwuvkSIrdHxMH17SOBm4FbgHkRMT0iZgF7A0vaVWCpev/otcAnM/Mb9eI7\nuqG/iDimnlSE6pdxA3Brve8YJnBvAJl5SGYelpmHAXcC7wOu6YZ/u9oHgLMBIuIFVG+a13XLvx+w\nmGpOYqi/HYF/2Rb9TbijpOjuS4h8Arignni6G7gsMwcjYiHVf4Ieqomrde0sstBpwM7AGRHxWWAQ\nOAU4twv6uxy4KCJuovodOhn4NXBhF/Q2nG76v7mI6t/vZqpR77FUn8q74t8vM6+OiDdExM+o6j4B\neJBt0J+XBpEkFZmIu6QkSW1gYEiSihgYkqQiBoYkqYiBIUkqYmBIkopMxPMwpLaIiD2ozhL+Vb2o\nh+r8kqMy8zdtK0waJwaGNDK/ycy57S5CagcDQxqjiNgHOJfqEgy7Amdn5lcj4nPA64AXUV3e/Xqq\nK8DOproA3smZeWd7qpZGzsCQRmb3iLidZ3dHfRPYHfhfmXljRLwE+DlVQED13S2vBIiIxcCJmfnz\niHgF1WVu9h73DqRRMjCkkdlsl1R9ef231Bck3JdqpDHkp/U6OwIHUF3DaOhS2jMiYpfMfGIc6pbG\nzMCQxu5SqovXXQV8C3hPw2Nr67+nAmsbwyYidjcsNJF4WK00Mj1Nlh0OfDYzr6L6SkwaRhEADH2j\nWUS8t378COCm1pYqbVuOMKSRaXZ55/8J/CgingASeAB4SZP13gucHxGfBJ4G/muripRawcubS5KK\nuEtKklTEwJAkFTEwJElFDAxJUhEDQ5JUxMCQJBUxMCRJRQwMSVKR/w9cAUrAnKZpxAAAAABJRU5E\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c10e290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### BONUS: Create your own question and answer it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
